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Fractals can catch cancer

Analyzing shapes of cell borders may prove useful in diagnosis

11:02am, October 7, 2013
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The geometric patterns known as fractals make for pretty pictures; one day they might help doctors diagnose cancers faster and more accurately.

Looking for a better alternative to the staining methods traditionally used on biopsied cells, Joachim Spatz and colleagues at the University of Heidelberg in Germany focused on patterns at the edges of pancreatic cancer cells. The group reported September 30 in Nano Letters that quantifying “fractalness” along individual cell borders allowed the researchers to distinguish between two types of cancer 97 percent of the time. Even in combination, the best staining techniques are right only about 85 times out of 100.

Staining tests rely on labeling molecules that bind in characteristic ways to cancer cells. After a biopsy, a doctor treats suspect cells with dyes and views the sample under a microscope. The size and shape of cells and their contents help the doctor identify cancer cells and distinguish between benign and malignant growths. In 1928, George Papanikolaou was among the first to use dye to identify cancer cells in a test known today as a Pap smear.

Despite their ubiquity, stains have drawbacks: They take time to prepare and analyze, and existing dyes can’t always reveal subtle differences between cells. Researchers have been looking for alternative tests that rely instead on cancer cells’ physical properties. Among these is adhesion, a cell’s ability to stick to its neighbors, which changes as tumors grow.

To reveal the fine detail along a single cell’s edge, Spatz and his team used a method called reflection interference contrast microscopy. Instead of shining light through the sample, the method bounces light off a cell to better show tiny structures along the cell’s edge that correlate with adhesion and other properties.

The group measured how much detail becomes apparent as you zoom in on the cell edge, a characteristic called fractal dimension. In an idealized fractal, a geometric pattern repeats infinitely as the viewing scale changes. Cancer cells have more fractalness than healthy cells, because uncontrolled growth produces chaotic protrusions large and small across the cell’s surface.

With two types of pancreatic cancer cells, one more malignant than the other, the fractal analysis missed the more dangerous cell only 3 percent of the time. The best single stain, by contrast, misses one-third to one-half of malignant cells.

Skipping stains could save time and money, according to Spatz and colleagues’ paper. It could also make cancer screenings easier to automate. The group envisions compiling data from cells analyzed by the fractal method into a library against which researchers could quickly compare new microscopic images.

The results are promising, but it’s much too early to know whether this type of test will ultimately prove better than staining, geneticist Charles Saxe says. “I wouldn’t necessarily say that that’s going to be the case,” he adds. “But I think they should continue at it.” Saxe, who directs the Cancer Cell Biology and Metastasis Center at the American Cancer Society, notes that researchers are also improving the diagnostic capacity of staining.


K. Klein et al. Marker-free phenotyping of tumor cells by fractal analysis of RICM images. Nano Letters. Posted Sept. 30, 2013. doi:10.1021/nl4030402

Further Reading

N. Seppa. Device offers promise of no brain tumor left behind. Science News. Vol.184, October 5, 2013, p.16.

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